NEUROSVM: An architecture to reduce the effect of the choice of kernel on the performance of SVM

Journal of Machine Learning Research

Volumn 10, Issue , 2009, Pages 591-622

  Ghanty, Pradip ^a   Paul, Samrat ^b   Pal, Nikhil R ^c  

^a Praxis Softek Solutions Pvt Ltd   (India)

^b IBM INDIA RESEARCH LAB   (India)

^c INDIAN STATISTICAL INSTITUTE   (India)

Author keywords

Averaging; Feature extraction; Hybrid system; Majority voting; Neural networks (NNs); Support vector machines (SVMs)

Indexed keywords

AVERAGING; BENCHMARK DATUM; ENSEMBLE METHODS; HYBRID ARCHITECTURES; INPUT SPACES; MAJORITY VOTING; MULTI LAYERS; MULTI-LAYERED; NON-LINEAR; PERCEPTRON; PROPOSED ARCHITECTURES; SUB-MODULES; SUPPORT VECTOR MACHINES (SVMS);

ELECTRIC GROUNDING; HYBRID COMPUTERS; IMAGE RETRIEVAL; NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS; SUPPORT VECTOR MACHINES;

FEATURE EXTRACTION;

EID: 64149128446     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Article

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